Scientific Portfolio & Projects

Goal: This project is a follow up work in which we constrain the Late w-M Transition Dark Energy model modifying MontePython, a program that performs MCMC calculations in order to calculate the best fit values of the parameters.

Details: Code

Goal: In this project a dark energy model that has a rapid transition of the equation of state parameter accompanied by a similar transition on the absolute magnitude is proposed as a possible solution to the Hubble tension. Using various cosmological data (such as Cosmic Microwave Background data, Baryon Acoustic Oscillation data, Type Ia Supernovae data as well as Cosmic Chronometer data) we identify the best fit values of the parameters of this model and pinpoint the physical predictions of the dark energy model in question. For the construction of the code Mathematica 12 was used.

Details: Mathematica Code

Goal: The goal of this project is to perform a data analysis of various cosmological models (such as the standard cosmological scenario and a modified gravity scenario with an evolving Newton's constant) using a compilation of 63 Redshift Space Distortion cosmological data. For the construction of the code Mathematica 10 was used.

Details: Mathematica Code

Goal: The goal of this project is to perform a short statistical analysis based on the xgoals (xG) statistic of three football clubs that compete in the Premier League (Manchester United, Manchester City and Liverpool) for the season 22/23. In a nutshell, the xG correspond to the number of goals that are expected to be scored by a team based on the field position and shot technique. Therefore, using this metric, a qualitative understanding of the performance of each team throughout the season is derived. The data for the three teams were obtained from understat.com and are analysed using Python, Excel and Mathematica.

Details: Python Code Excel Code Mathematica Code